WO2016162863A1 - Qualitatively planning, measuring, making effecient and capitalizing on marketing strategy - Google Patents
Qualitatively planning, measuring, making effecient and capitalizing on marketing strategy Download PDFInfo
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- WO2016162863A1 WO2016162863A1 PCT/IL2015/050382 IL2015050382W WO2016162863A1 WO 2016162863 A1 WO2016162863 A1 WO 2016162863A1 IL 2015050382 W IL2015050382 W IL 2015050382W WO 2016162863 A1 WO2016162863 A1 WO 2016162863A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0242—Determining effectiveness of advertisements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0282—Rating or review of business operators or products
Definitions
- the present invention relates to the field of marketing strategies analyzing systems. More particularly, the invention relates to a fully- automated platform enabling vendors— mainly of the FMCG (Fast Moving Consumer Goods) sector - to qualitatively plan, measure, make efficient, and capitalize on their marketing strategies and commercial campaigns— ahead of time, before going air and spending an ⁇ ' money.
- FMCG Frest Moving Consumer Goods
- the “Human Factor” may refer to the followings:
- Measuring qualitative metrics loyalty, trust, passion, interaction, and brand awareness
- Measuring quantitative metrics reach, volume of posts, conversations surround the brand, and influencers engagement; Integrating Human Intuition, Expertise, and Usable Knowledge; Interfacing with Social Media, enabling analysis of the social conversation surround a Product or a Service;
- a Marketing/Strategy manager would need to perform an elaborated and time consuming analysis to figure out incremental gain in sales by increasing the respective marketing element by one unit.
- the Marketing/Strategy manager would need to optimize the marketing resources—that is, budget, time, and headcount—and identify the efficient marketing activities.
- the present invention relates to a fully- automated method, in a data mining and data processing system, for defining and qualitatively planning, measuring, and making efficient marketing strategies/commercial campaign.
- the method comprising dynamically obtaining - by a data mining subsystem — information related to marketing strategy/commercial campaign; analyzing — by a data processing subsystem - said information, in real-time and offline, to identify patterns; selecting— by said data processing subsystem - relevant patterns from said identified patterns to define a marketing strategjr/commercial campaign for a customer; and defining— by said data processing subsystem - a marketing strategy/commercial campaign based on said selected patterns and addressed to a specific brand— product or service - of a specific customer, which playing in a specific sector, of a specific country, at a specific time.
- the method includes qualitatively measuring - ahead of time, before going air— the efficiency of marketing strategies/commercial campaigns.
- the method further comprises using validity and reliability analysis methods.
- the method further comprises self-learning mechanism— enhancing both the validity and Reliability of the system.
- the method further comprises Post-Mortem analyzing - at the end of the marketing strategy/commercial campaign of a specific sector - and amending the system predefined reference metrics of this sector accordingly.
- the method further comprises integrating human intuition, expertise, and usable knowledge.
- the method further comprises interfacing with social media, thereby enabling: analyzing the social conversation surround a Product or a Service, measuring qualitative metrics— loyalty, trust, passion, interaction, and brand awareness, and measuring quantitative metrics— reach, volume of posts, conversations surround the brand, and influencers engagement.
- the method further comprises providing geo-locational, geographic, demographic, and psychographic insights— enabling full control over what is really relevant to the audience.
- the method further comprises constantly alerting and updating— and automatically— the marketing strategy/commercial campaign managers about new discoveries and insights concerning their needs.
- the method further comprises providing reactive decision making while the marketing strategy/commercial campaign is running, thereby enabling responding— across all channels — on-the-fly, changing/modifying the marketing strategy/commercial campaign in real time, and affecting the results accordingly.
- the method further comprises providing evidence-based, actionable insights to essential business question.
- the method of the present may enable the following features:
- obtaining information related to marketing strategy/commercial campaign further comprises: ensuring reliability and validating expected data metrics of a marketing strategy/commercial campaign - based on a self-learning mechanism - by examining their correlation with predefined reference metrics, and fine tuning these values accordingly, thereby ensuring that the current marketing strategy/commercial campaign is constantly valid, reliable, efficient and qualitative measurability.
- obtaining information related to marketing strategy/commercial campaign comprises: performing data mining operations to collect customer interaction information from a plurality of sources - both in real-time (online) and offline.
- the data mining operations comprise data retrieval form external sources including social media and professional databases.
- the customer interactions comprise at least one of a brand— product or service— review, a review comment, a post, a comment, various types of digital feedbacks, or interconnected documents and other digital conversations.
- analyzing the information to identify patterns comprises: identifying parameters based on their current values and computing foreseen values of these parameters, and accordingly providing relevant trends— business, commercial, trade, geo- locational, geographic, demographic, and psychographic - both domestic and international, that may affect the marketing strategy/commercial campaign.
- analyzing the information to identify patterns further comprises: analyzing the parameters at the end of the marketing strategy/commercial campaign of a specific sector and amending the system predefined reference metrics of this sector accordingly — as known as Post-Mortem Analysis, thereby ensuring validity and reliability.
- analyzing the information to identify patterns comprises: qualitatively and efficiently identifying a set of influencing parameters, wherein the set of influencing parameters is used by a vendor to define marketing strategies for a set of customers.
- the method further comprises allowing the integration of human intuition, expertise, and usable knowledge, and accordingly providing most up-to-date, valid, and reliable Marketing Strategy/Commercial Campaign.
- the method further comprises creating evidence-based, actionable insights to essential business questions, by the data processing and data mining.
- the creation of the actionable insights includes one or more of: fully-automated and continually gathering information from many sources - both in real time and offline, capturing a 360 degree view around the product or service, monitoring the social conversation surround the product/service, filtering the top relevant information only, identifying hidden patterns - by analyzing huge amount of information and intelligence, and over long time, in-depth, competitive analysis, continually analyzing/reanalyzing the information, and comparing the results to the real world— ensuring the system is always valid and reliable, micro-assessment of strengths, weaknesses, opportunities, an threats, identifying and alerting vulnerabilities, identifying and alerting edge advantages, minimizing risks and maximizing" opportunities by early discovering and alerting, reactive decision making, Post-Mortem analysis - enhancing the validity and reliabil y of the system, cross-checking with insights generated for other analysis of the same sector and/or country— enhancing the validity and reliability of the system.
- the method further comprises providing an operational Reactive Decision Making module while the marketing strategy/commercial campaign is running, thereby enabling responding - across all channels - on-the-fly, changing/modifying the marketing strategy/commercial campaign in real time, and affecting the results accordingly.
- fully- automatically and qualitatively defining a marketing strategy based on the selected patterns comprises: dynamically identifying at least one of channels associated with a segment of brands either products or services; identifying marketing strategies of a vendor associated with a segment of brands based on current business, commercial, trade, geo-locational, geographic, demographic, and psychographic factors that are associated with a customer and a most efficient channel to reach the customer for the segment of said brands; and presenting to a client associated with a customer, a set of marketing strategies defined by a vendor for the segment of said brands ranked list.
- the present invention relates to a system, which comprises: at least one processor; and a memory comprising computer- readable instructions which when executed by the at least one processor causes the processor to execute a data processing system for defining and qualitatively measuring marketing strategies/commercial campaign, wherein the system:
- a marketing strateg3'/commercial campaign based on said selected patterns and addressed to a specific brand— product or service - of a specific customer, which playing in a specific sector, of a specific country, at a specific time.
- a non-transitory computer-readable medium comprising instructions which when executed b ⁇ ' at least one processor causes the processor to perform the fully-automated method, in a data mining and data processing system, of defining and qualitatively planning, measuring, and making efficient marketing strategies/commercial campaign.
- FIG. 1 schematically illustrates a high-level architecture of a system for fully-automated and qualitatively planning, measuring, making efficient and capitalizing on marketing strategies and commercial campaigns, according to an embodiment of the invention
- FIG. 2 schematically illustrates central analysis database architecture, according to an embodiment of the invention
- UMMD Universal Macro Metrics Database
- SMMD Sectorial Micro Metrics Database
- Fig. 5 schematically illustrates a Customer Social Media Metrics Database (CSMM), according to an embodiment of the invention
- CNMD Customer Nano Metrics Database
- FIG. 7 schematically illustrates the system's layers, according to an embodiment of the invention .
- data processing refers herein to the tasks of: gathering massive amount of data (the data can be of many types and formats, and from many different sources) both in real time and offline; transforming this data into 'legible', 'understood', usable, and accessible items; and ultimately organizing this data in a pre-defined databases.
- data processing stage there is usually too much 'data', but not enough 'information'. Therefore, the next stage of data mining is required.
- data mining refers to herein to the tasks of performing a series of powerful analysis tools on this processed data— identifying hidden patterns, and ultimately converting this information and intelligence into key discoveries, actionable insights, and predicted behavior.
- Fig. 1 schematically illustrates a high-level architecture of a system 100 for fully- automated and qualitatively planning, measuring, making efficient and capitalizing on marketing strategies and commercial campaigns, according to an embodiment of the invention.
- System 100 comprises a Central Archive and Analysis Database (CAAD) 120, and plurality of subsystem modules 101-109 that communicates with CAAD 108, such as Database Manager 101, Validator 102, Strategy Analyzer 103, Campaign Analyzer 104, Forecaster 105, Decision Maker 106, Post- Mortem Analyzer 107, Administration Console 108, and Application Programming Interface (API) 109 for handling third party data from external sources such as Social Media 110 and Professional Databases 111.
- CAAD 120 process and analyzes the data (i.e., performs data processing and data mining) from the subsystem modules and accordingly outputs business and marketing insights 113, statistics and reports 114.
- CAAD 120 is a Relational Data Base Management System (RDBMS) containing all the relevant information — static and dynamic (those changing over time)— about all the Marketing Strategies and Commercial Campaigns, previous and currently running. CAAD 120 is the basis for working of all the other subsystems within system 100.
- RDBMS Relational Data Base Management System
- CAAD 120 may contain the following databases:
- analytics 125 is adapted to handle the data stored in the databases 121-124.
- 125 is representing all the analyzing subsystems, that is, 102, 103, 104, 104, 105, 106, and 107.
- Fig. 3 schematically illustrates a 3-dimenal matrix the outlines the UMMD 121, according to an embodiment of the invention.
- UMMD 121 may include data representing Country-Related information such as Consumer Price Index, Cost of Building Index, Annual Growth Rate, Annual Inflation, Gross Domestic Product, Average Income, Population Size, Population Density, Average Family Size, birth Rate, etc.
- Table 1 outlines an exemplary data type of different fields that may be included in UMMD 121:
- SMMD 122 may include data representing Sector-Related information such as Annual/Quarterly Growth Rate, Annual/Quarterly Revenues, Annual/Quarterly Sales, Annual/Quarterly Gross Profit, Annual/Quarterly Operating Profit, Multiplier, Equity Capital/Operating Capital Ratio, Total Production Per Product, Consumption Per Product, Consumption Per Person/Product, Total Stocks Per Product, Trade Balance Per Product, Production Trends, Consumption Trends, etc.
- Sector-Related information such as Annual/Quarterly Growth Rate, Annual/Quarterly Revenues, Annual/Quarterly Sales, Annual/Quarterly Gross Profit, Annual/Quarterly Operating Profit, Multiplier, Equity Capital/Operating Capital Ratio, Total Production Per Product, Consumption Per Product, Consumption Per Person/Product, Total Stocks Per Product, Trade Balance Per Product, Production Trends, Consumption Trends, etc.
- Table 2 outlines an exemplary data type of different fields that may be included in SMMD 122:
- Fig. 5 schematically illustrates a 3-dimenal matrix the outlines the CSMM 123, according to an embodiment of the invention.
- CSMM 123 may include data representing Social Media Related information such as What are the Added Values, What would be Added Values, Brand Strengths, Brand Weaknesses, What Seems Threating, No-Meet Needs, No-Meet Features, Brand Recognition, Consumer Segmentation, 'Volume' of Positive/Negative Feedback, Opinion Influencers' Feedback, High Caliber Bloggers' Feedback, etc.
- Table 3 outlines an exemplary data type of different fields that may be included in CSMM 123:
- Fig. 6 schematically illustrates a 3-dimenal matrix the outlines the CNMD 124, according to an embodiment of the invention.
- CNMD 124 may include data representing Customer-Related information such as Annual/Quarterly Growth Rate, Annual/Quarterly Revenues, Annual/Quarterly Sales, Annual/Quarterly Gross Profit, Annual/Quarterly Operating Profit, Equity Capital, Operating Capital, Revenue per Share, Multiplier, CAGR (Compound Annual Growth Rate), EBITDA (Earning Before Interest, Tax, Depreciation and Amortization), etc.
- CAGR Compound Annual Growth Rate
- EBITDA Errning Before Interest, Tax, Depreciation and Amortization
- Table 4 An exemplary IP related data is shown by following Table 5:
- - Events Manager A software module that allows performing basic tasks with databases, like Create, Delete, Update, Insert, Open, Save, Alert, Drop, logon, Logoff, Startup, Shutdown, etc., as well as accessing records and fields within a database.
- Triggers Manager A software module maintaining the integrity of the information on the databases, by containing stored procedures that configured to automatically execute in response to certain events take place on particular table or view in a database.
- the validator 102 validates the expected metrics of a Marketing Strategy/Commercial Campaign by examining their correlation with predefined reference metrics of system 100, and fine tuning these values accordingly. In Addition, it ensures that the current Marketing Strategy/Commercial Campaign is constantly valid and reliable - and notifying the Decision Maker module accordingly.
- One of the core elements of system 100 is a Self-Learning mechanism which used to enhance both the validity and reliability of the system. Reliability is ensured by observing the overall consistency and repeatability of the various measures/metrics and checking if they produce similar results under consistent conditions.
- the reference metrics can be a pre-modeling marketing data having a plurality of marketing variables, wherein each of the plurality of marketing variables associated with marketing strategies for one or more products/services.
- the marketing variables include, but are not limited to, sales data captured over a period of time for products, parameters indicating the time/season of the year, macroeconomic parameters such as total income of individuals in a selected market region and marketing variables such as number of advertisements of the products through various communication channels, number of users visiting a Website of stores selling the products. It would be appreciated by those skilled in the art that a variety of such marketing parameters may be envisaged.
- Strategy Analyzer 103 analyzes on-line the entire marketing strategy for providing results at each single criteria of a marketing strategy, such as brand (product or service) perception, brand strengths and weaknesses, key opinion leader mapping, market's real needs and unaddressed consumers' needs, competitive intelligence (competitor and brand mapping, pricing, perception, strengths, weaknesses, innovation, technologies), competitors' reaction (offering, pricing, packaging, campaigns, etc.), market maturity indicators, market key drives and challenges, market disruptive trends, regulatory and compliancy indicators, technology landscape, innovation threats, IP (Intellectual Property) strengths and weaknesses, most attractive target markets, new opportunities, competitive brand positioning, best offering, most recommended business/strategic partnerships, etc.
- brand product or service
- IP Intelligent Property
- Campaign Analyzer 104 performs on-line analyzing of an entire given commercial campaign, and accordingly it may provide data results for each single criteria of this commercial campaign.
- Forecaster 105 Based on present values of various parameters - such as sales, consumer segmentation by various breakdowns, pricing, etc., Forecaster 105 computes the foreseen values of these parameters, and accordingly provides relevant trends, both domestic and international, that may affect the marketing strategy/commercial campaign.
- Decision Maker 106 provides critical business, strategic, and operational reactive decision making, based on Artificial Intelligence (AI) methodologies—such as improving go-to-market plan, hit market faster, marketing plan reassessment, pricing strategy reassessment, sales plan reassessment, sales force effectiveness, etc.— in the course of an active marketing strategy/commercial campaign - according to the results of Validator 102.
- AI Artificial Intelligence
- the Decision Maker module 106 enables the customer to respond across all channels on-the-fly, in real time — while the marketing strategy/commercial campaign is running - and affecting the results accordingly, by changing/modifjdng the marketing strategy/commercial campaign.
- Post-Mortem Analyzer 107 performs offline comprehensive and in-depth analysis— at the end of the marketing strategy/commercial campaign of a specific sector - and accordingly amends the system predefined reference metrics of this sector:
- Non-Trivial Patterns analyzing those patterns which need long time of observation and follow-up in order to conclude insights accordingly - such as phenomena happen only at a specific day in a month/week, or at a specific hour in a day, or at a specific geography, or for a very specific gender, etc.
- Marketing strategy/commercial campaign launch time (e.g., month during the year, season during the year, any other special event during the year, etc.);
- Marketing Media Channels e.g., Resellers, Retailers, Point of Sales, Television, Cinema, Print media. Interactive Billboard, Social Networks, IVR [Interactive Voice Response]);
- Demographic Profile e.g., Place of Living such as City/Town/Village, North/East/South/West, etc.
- APIs 109 recognizes that every third party vendor has its own unique process and workflow requirements - this subsystem contains a set of open and fully standards compliant APIs (Application Programming Interface) providing the modularity to build a highly flexible best-in-class ecosystem.
- This module may contain APIs with the following third party subs3 ⁇ stems:
- a Social Media API module 110 that transforms multiple unclassified social online data - which is proven to be an ultimate source for intelligence— into purposeful intelligence findings:
- Measuring quantitative metrics reach, volume of posts, conversations surround the brand, and influencers engagement
- the Social Media API module 110 gathers data that can be collected from a wide range of available web-based sources such as social networks, news publications, magazines, high-caliber blogs, consumer discussions, career websites, etc. Interfacing with Social Media 110 enables to provide an analysis of the social conversation surround a product or service.
- Administration Console 108 is software based application that provides a powerful graphical tool, which may enable the following:
- Administration Console 108 provides an intuitive data visualization, in various breakdowns, that is easy to interpret and easy to act on— giving insights into the hearth of the system at variety of aspects, such as:
- Multi-Level e.g., specific marketing media, a group of marketing media, entire marketing strategy life, entire commercial campaign life
- Multi-Period e.g., Daily /Weekly /Monthly/Quarterly, entire marketing strategy/commercial campaign period, user defined
- - Multi-Format e.g., table, pie chart, bar chart, graph.
- the business and marketing insights module 112 provides intuitive insights visualization that is easy to interpret and easy to act on - addressing a wide range of highly valuable business and marketing missions:
- Competitors' Reaction Offering, Pricing, Packaging, Campaigns, etc.
- the Business and Marketing Insights module 112 may provide its outcomes in various breakdowns:
- EU European Union
- OECD Organization for Economic Co-operation and Development
- BRICS Brazil, Russia, India, China, South Africa
- Developed countries Developing countries, Worldwide
- CAAD 120 and the subsystems modules of system 100 are implemented by program modules that may include routines, programs, components, data structures, and other t ⁇ pes of structures that perform particular tasks or implement particular abstract data types in system 100.
- program modules may include routines, programs, components, data structures, and other t ⁇ pes of structures that perform particular tasks or implement particular abstract data types in system 100.
- the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like.
- the invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network.
- program modules may be located in both local and remote memory storage devices.
- Embodiments of the invention may be implemented as a computer process (method), a computing system, or as an article of manufacture, such as a computer program product or computer readable media.
- the computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process.
- the computer program product may also be a propagated signal on a carrier readable by a computing system and encoding a computer program of instructions for executing a computer process.
- Fig. 7 schematically illustrates system 100 is a top level layer form, according to an embodiment of the invention.
- the layer form includes a data storage layer 73 that performs data mining using CAAD 120, a business logic laj ⁇ e 72 that perform data processing and a presentation layer 71 that provides the data to the user.
Abstract
The present invention relates to a fully-automated method, in a data mining and data processing system, for defining and qualitatively planning, measuring, and making efficient marketing strategies/commercial campaign. The method comprising dynamically obtaining by a data mining subsystem information related to marketing strategy/commercial campaign; analyzing by a data processing subsystem - said information, in real-time and offline, to identify patterns; selecting by said data processing subsystem relevant patterns from said identified patterns to define a marketing strategy/commercial campaign for a customer; and defining by said data processing subsystem a marketing strategy/commercial campaign based on said selected patterns and addressed to a specific brand - product or service of a specific customer, which playing in a specific sector, of a specific country, at a specific time.
Description
QUALITATIVELY PLANNING, MEASURING, MAKING
EFFECIENT AND CAPITALIZING ON MARKETING STRATEGY
Field of the Invention
The present invention relates to the field of marketing strategies analyzing systems. More particularly, the invention relates to a fully- automated platform enabling vendors— mainly of the FMCG (Fast Moving Consumer Goods) sector - to qualitatively plan, measure, make efficient, and capitalize on their marketing strategies and commercial campaigns— ahead of time, before going air and spending an}' money.
Background of the invention
Marketing is a hundreds-billion dollar global industry, and Marketing and Strategy managers are all making critical decisions with less data and discipline than they apply to negligible decisions in other aspects of their businesses. They are lack an industry standard for measurement. The}' need a method to determine the efficiency of their efforts. They need to measure how efficient their marketing strategies and commercial campaigns are at influencing purchase intent— the ultimate goal.
Hundreds of thousands of new products are launched to the market every year. The vast majority of new products fail within two years. And almost all of all innovations fail to return their cost of capital.
Enterprise vendors, manufacturers, suppliers, as well as governmental and national/public organizations are increasingly exploring the possibilities of reaching maximum end users, by dramatically increasing investments in marketing strategies and commercial campaigns over a wide range of media, offline and online.
The technology is now available to do that. However, efficient measurability and human factor are vital elements for successful marketing strategies and commercial campaigns, enabling the companies to capitalize on their investments.
The "Human Factor" may refer to the followings:
Highly considering the user experience in real time— providing the marketing strategies/commercial campaigns managers with direct consideration of the end users' response, and having their immediate effect on the commercial campaigns look and feel and marketing strategies results;
Measuring qualitative metrics— loyalty, trust, passion, interaction, and brand awareness;
Measuring quantitative metrics — reach, volume of posts, conversations surround the brand, and influencers engagement; Integrating Human Intuition, Expertise, and Usable Knowledge; Interfacing with Social Media, enabling analysis of the social conversation surround a Product or a Service;
Tracking new discoveries and insights - and constantly alerting accordingly;
Providing geo-locational, geographic, demographic, and psychographic insights— enabling full control over what is really relevant to the audience; and
Providing evidence-based insights.
Lack of a solution meeting the above unique and strict requirements may results in:
High costs of marketing strategies and commercial campaigns;
Poor ROI (Return On Investment);
Negative impact on profitability; and
Customers dissatisfaction and high churn.
Typically, a Marketing/Strategy manager would need to perform an elaborated and time consuming analysis to figure out incremental gain in sales by increasing the respective marketing element by one unit. In addition, the Marketing/Strategy manager would need to optimize the marketing resources— that is, budget, time, and headcount—and identify the efficient marketing activities.
Unfortunately, analyzing marketing data to determine marketing strategies is extremely complex due to difficulties in capturing and extracting data from various data sources. Furthermore, business management often requires forecasting future outcomes of the sales/revenues based on changes in marketing strategies including variations in spends towards various marketing channels. For any given business, there are a large number of factors that influence the business outcome. Many business organizations generate forecasts through a manual process, which can be extremely cumbersome and time- consuming.
Furthermore, since it is currently being done through a manually process - it never could be a valid and reliable one.
Therefore, it is desirable to develop a fully-automated platform to organize, integrate and analyze marketing and business data to generate valid and reliable marketing strategies and commercial campaigns solutions for optimizing spend towards different marketing channels, different target markets, different geographies, different cultures, and at different economics climates.
It is an object of the present invention to provide a fully-automated platform which is capable of converting information and intelligence into key discoveries and actionable insights aligned with the customer's particular and evolving business and marketing needs.
It is another object of the present invention to provide a platform capable of providing evidence-based, actionable insights to essential business questions.
Other objects and advantages of the invention will become apparent as the description proceeds.
Summary of the Invention
The present invention relates to a fully- automated method, in a data mining and data processing system, for defining and qualitatively planning, measuring, and making efficient marketing strategies/commercial campaign. The method comprising dynamically obtaining - by a data mining subsystem — information related to marketing strategy/commercial campaign; analyzing — by a data processing subsystem - said information, in real-time and offline, to identify patterns; selecting— by said data processing subsystem - relevant patterns from said identified patterns to define a marketing strategjr/commercial campaign for a customer; and defining— by said data processing subsystem - a marketing strategy/commercial campaign based on said selected patterns and addressed to a specific brand— product or service - of a specific customer, which playing in a specific sector, of a specific country, at a specific time.
According to an embodiment of the invention, the method includes qualitatively measuring - ahead of time, before going air— the efficiency of marketing strategies/commercial campaigns.
According to an embodiment of the invention, the method further comprises using validity and reliability analysis methods.
According to an embodiment of the invention, the method further
comprises self-learning mechanism— enhancing both the validity and Reliability of the system.
According to an embodiment of the invention, the method further comprises Post-Mortem analyzing - at the end of the marketing strategy/commercial campaign of a specific sector - and amending the system predefined reference metrics of this sector accordingly.
According to an embodiment of the invention, the method further comprises integrating human intuition, expertise, and usable knowledge.
According to an embodiment of the invention, the method further comprises interfacing with social media, thereby enabling: analyzing the social conversation surround a Product or a Service, measuring qualitative metrics— loyalty, trust, passion, interaction, and brand awareness, and measuring quantitative metrics— reach, volume of posts, conversations surround the brand, and influencers engagement.
According to an embodiment of the invention, the method further comprises providing geo-locational, geographic, demographic, and psychographic insights— enabling full control over what is really relevant to the audience.
According to an embodiment of the invention, the method further comprises constantly alerting and updating— and automatically— the marketing strategy/commercial campaign managers about new discoveries and insights concerning their needs.
According to an embodiment of the invention, the method further comprises providing reactive decision making while the marketing strategy/commercial campaign is running, thereby enabling responding— across all channels — on-the-fly, changing/modifying the marketing
strategy/commercial campaign in real time, and affecting the results accordingly.
According to an embodiment of the invention, the method further comprises providing evidence-based, actionable insights to essential business question.
The method of the present may enable the following features:
Capturing a 360 degree view around a Product or a Service;
Efficiency optimization of existing marketing strategies/commercial campaigns;
Generic and High Longevity platform — well designed to meet particular and evolving customers' needs;
Cloud-Based Solution - dramatically saving CAPEX and OPEX costs;
Enabling cross-strategy/cross-campaign — a joint marketing strategy/commercial campaign of different Products/Services addressed to the same target market concurrently.
Delivering the right message, at the right time, to the right audience, and by the right channels; and
Faster time to business and marketing insights.
According to an embodiment of the invention, obtaining information related to marketing strategy/commercial campaign further comprises: ensuring reliability and validating expected data metrics of a marketing strategy/commercial campaign - based on a self-learning mechanism - by examining their correlation with predefined reference metrics, and fine tuning these values accordingly, thereby ensuring that the current marketing strategy/commercial campaign is constantly valid, reliable, efficient and qualitative measurability.
According to an embodiment of the invention, further comprises applying
artificial intelligent algorithms on the fine-tuned data— as part of the self- learning mechanism - thereby providing valid and reliable strategic.
According to an embodiment of the invention, obtaining information related to marketing strategy/commercial campaign comprises: performing data mining operations to collect customer interaction information from a plurality of sources - both in real-time (online) and offline.
According to an embodiment of the invention, the data mining operations comprise data retrieval form external sources including social media and professional databases.
According to an embodiment of the invention, the customer interactions comprise at least one of a brand— product or service— review, a review comment, a post, a comment, various types of digital feedbacks, or interconnected documents and other digital conversations.
According to an embodiment of the invention, analyzing the information to identify patterns comprises: identifying parameters based on their current values and computing foreseen values of these parameters, and accordingly providing relevant trends— business, commercial, trade, geo- locational, geographic, demographic, and psychographic - both domestic and international, that may affect the marketing strategy/commercial campaign.
According to an embodiment of the invention, analyzing the information to identify patterns further comprises: analyzing the parameters at the end of the marketing strategy/commercial campaign of a specific sector and amending the system predefined reference metrics of this sector accordingly — as known as Post-Mortem Analysis, thereby ensuring validity and reliability.
According to an embodiment of the invention, analyzing the information to identify patterns comprises: qualitatively and efficiently identifying a set of influencing parameters, wherein the set of influencing parameters is used by a vendor to define marketing strategies for a set of customers.
According to an embodiment of the invention, the method further comprises allowing the integration of human intuition, expertise, and usable knowledge, and accordingly providing most up-to-date, valid, and reliable Marketing Strategy/Commercial Campaign.
According to an embodiment of the invention, the method further comprises creating evidence-based, actionable insights to essential business questions, by the data processing and data mining.
According to an embodiment of the invention, the creation of the actionable insights includes one or more of: fully-automated and continually gathering information from many sources - both in real time and offline, capturing a 360 degree view around the product or service, monitoring the social conversation surround the product/service, filtering the top relevant information only, identifying hidden patterns - by analyzing huge amount of information and intelligence, and over long time, in-depth, competitive analysis, continually analyzing/reanalyzing the information, and comparing the results to the real world— ensuring the system is always valid and reliable, micro-assessment of strengths, weaknesses, opportunities, an threats, identifying and alerting vulnerabilities, identifying and alerting edge advantages, minimizing risks and maximizing" opportunities by early discovering and alerting, reactive decision making, Post-Mortem analysis - enhancing the validity and reliabil y of the system, cross-checking with insights generated for other analysis of the same sector and/or country— enhancing the validity and reliability of the system.
According to an embodiment of the invention, the method further comprises providing an operational Reactive Decision Making module while the marketing strategy/commercial campaign is running, thereby enabling responding - across all channels - on-the-fly, changing/modifying the marketing strategy/commercial campaign in real time, and affecting the results accordingly.
According to an embodiment of the invention, fully- automatically and qualitatively defining a marketing strategy based on the selected patterns comprises: dynamically identifying at least one of channels associated with a segment of brands either products or services; identifying marketing strategies of a vendor associated with a segment of brands based on current business, commercial, trade, geo-locational, geographic, demographic, and psychographic factors that are associated with a customer and a most efficient channel to reach the customer for the segment of said brands; and presenting to a client associated with a customer, a set of marketing strategies defined by a vendor for the segment of said brands ranked list.
In another aspect, the present invention relates to a system, which comprises: at least one processor; and a memory comprising computer- readable instructions which when executed by the at least one processor causes the processor to execute a data processing system for defining and qualitatively measuring marketing strategies/commercial campaign, wherein the system:
- dynamically obtains— by a data mining subsystem — information related to marketing strategy/commercial campaign;
- analyzes - by a data processing subsystem - said information, in real-time and offline, to identify patterns;
- selects— by said data processing subsystem— relevant patterns from said identified patterns to define a
marketing strategy/commercial campaign for a customer; and
defines - by said data processing subsystem— a marketing strateg3'/commercial campaign based on said selected patterns and addressed to a specific brand— product or service - of a specific customer, which playing in a specific sector, of a specific country, at a specific time.
In another aspect, a non-transitory computer-readable medium comprising instructions which when executed b}' at least one processor causes the processor to perform the fully-automated method, in a data mining and data processing system, of defining and qualitatively planning, measuring, and making efficient marketing strategies/commercial campaign.
Brief Description of the Drawings
In the drawings:
- Fig. 1 schematically illustrates a high-level architecture of a system for fully-automated and qualitatively planning, measuring, making efficient and capitalizing on marketing strategies and commercial campaigns, according to an embodiment of the invention;
- Fig. 2 schematically illustrates central analysis database architecture, according to an embodiment of the invention;
- Fig. 3 schematically illustrates a Universal Macro Metrics Database (UMMD), according to an embodiment of the invention;
- Fig. 4 schematically illustrates a Sectorial Micro Metrics Database (SMMD), according to an embodiment of the invention;
Fig. 5 schematically illustrates a Customer Social Media Metrics Database (CSMM), according to an embodiment of the invention;
- Fig. 6 schematically illustrates a Customer Nano Metrics Database (CNMD), according to an embodiment of the invention; and
- Fig. 7 schematically illustrates the system's layers, according to an embodiment of the invention .
Detailed Description of the Invention
The term "data processing" refers herein to the tasks of: gathering massive amount of data (the data can be of many types and formats, and from many different sources) both in real time and offline; transforming this data into 'legible', 'understood', usable, and accessible items; and ultimately organizing this data in a pre-defined databases. Following the data processing stage, there is usually too much 'data', but not enough 'information'. Therefore, the next stage of data mining is required.
In this context, the term "data mining" refers to herein to the tasks of performing a series of powerful analysis tools on this processed data— identifying hidden patterns, and ultimately converting this information and intelligence into key discoveries, actionable insights, and predicted behavior.
Reference will now be made to several embodiments of the present invention, examples of which are illustrated in the accompanying figures. Wherever practicable similar or like reference numbers may be used in the figures and may indicate similar or like functionality. The figures depict embodiments of the present invention for purposes of illustration only. One skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the invention described herein.
Fig. 1 schematically illustrates a high-level architecture of a system 100 for fully- automated and qualitatively planning, measuring, making efficient and capitalizing on marketing strategies and commercial campaigns, according to an embodiment of the invention. System 100 comprises a Central Archive and Analysis Database (CAAD) 120, and plurality of subsystem modules 101-109 that communicates with CAAD
108, such as Database Manager 101, Validator 102, Strategy Analyzer 103, Campaign Analyzer 104, Forecaster 105, Decision Maker 106, Post- Mortem Analyzer 107, Administration Console 108, and Application Programming Interface (API) 109 for handling third party data from external sources such as Social Media 110 and Professional Databases 111. CAAD 120 process and analyzes the data (i.e., performs data processing and data mining) from the subsystem modules and accordingly outputs business and marketing insights 113, statistics and reports 114.
CAAD 120 is a Relational Data Base Management System (RDBMS) containing all the relevant information — static and dynamic (those changing over time)— about all the Marketing Strategies and Commercial Campaigns, previous and currently running. CAAD 120 is the basis for working of all the other subsystems within system 100.
Referring now to Fig. 2, an exemplary CAAD 120 architecture is shown in accordance with an embodiment of the invention. According to this exemplary embodiment, CAAD 120 may contain the following databases:
- Universal Macro Metrics Database (UMMD) 121;
- Sectorial Micro Metrics Database (SMMD) 122;
- Customer Social Media Metrics Database (CSMM) 123; and
- Customer Nano Metrics Database (CNMD) 124.
Where analytics 125 is adapted to handle the data stored in the databases 121-124. 125 is representing all the analyzing subsystems, that is, 102, 103, 104, 104, 105, 106, and 107.
Fig. 3 schematically illustrates a 3-dimenal matrix the outlines the UMMD 121, according to an embodiment of the invention. UMMD 121 may include data representing Country-Related information such as Consumer Price Index, Cost of Building Index, Annual Growth Rate, Annual Inflation, Gross Domestic Product, Average Income, Population
Size, Population Density, Average Family Size, Birth Rate, etc.
The following Table 1 outlines an exemplary data type of different fields that may be included in UMMD 121:
Table 1
Fig. 4 schematically illustrates a 3-dimenal matrix the outlines the SMMD 122, according to an embodiment of the invention. SMMD 122 may include data representing Sector-Related information such as Annual/Quarterly Growth Rate, Annual/Quarterly Revenues, Annual/Quarterly Sales, Annual/Quarterly Gross Profit, Annual/Quarterly Operating Profit, Multiplier, Equity Capital/Operating Capital Ratio, Total Production Per Product, Consumption Per Product, Consumption Per Person/Product, Total Stocks Per Product, Trade Balance Per Product, Production Trends, Consumption Trends, etc.
The following Table 2 outlines an exemplary data type of different fields that may be included in SMMD 122:
Field Data Type
Annual Growth Rate Decimal (x.yz%)
Quarterly Growth Rate Decimal (x.yz% x Q1/Q2/Q3/Q4)
Annual Revenues Integer
Quarterly Revenues Integer (x Q1/Q2/Q3/Q4)
Annual Sales Integer
Quarterly Sales Integer (x Q1/Q2/Q3/Q4)
Annual Gross Profit Integer
Quarterly Gross Profit Integer (x Q1/Q2/Q3/Q4)
Annual Operating Profit Integer
Quarterly Operating Profit Integer (x Q1/Q2/Q3/Q4)
Multiplier Decimal (x.y)
Equity Capital/Operating Capital Ratio Decimal (x.yz)
Total Production Per Product Integer
Total Consumption Per Product Integer
Consumption Per Person/Product Decimal (x.yz)
Total Stocks Per Product Integer
Trade Balance Per Product Integer
Production Trends Text
Consumption Trends Text
Average Monthly Salary Integer
Number of Employees Integer
Rate of Employees Growth Decimal (x.y%)
Transport Margin Integer
Trade Margin Integer
Direct Coefficients Decimal (x.yz%)
Total Coefficients Decimal (x.yz%)
Value Added Tax Decimal (x.y%)
Sales Tax Decimal (x.y%)
Gross Value Added Integer
Index of Industrial Production Decimal (x.y)
Gross Output of the Manufacturing
Integer
Industry
Table 2
Fig. 5 schematically illustrates a 3-dimenal matrix the outlines the CSMM 123, according to an embodiment of the invention. CSMM 123 may include data representing Social Media Related information such as What are the Added Values, What would be Added Values, Brand Strengths, Brand Weaknesses, What Seems Threating, No-Meet Needs, No-Meet Features, Brand Recognition, Consumer Segmentation, 'Volume' of Positive/Negative Feedback, Opinion Influencers' Feedback, High Caliber Bloggers' Feedback, etc.
The following Table 3 outlines an exemplary data type of different fields that may be included in CSMM 123:
Field Data Tvpe
Brand Text
Date DDMMYYYY
What are the Added Values Text List— By Priority
What would be Added Values Text List - By Priority
Brand Strengths Text List— By Priority
Brand Weaknesses Text List - By Priority
What Seems Threating Text List - By Priority
No-Meet Needs Text List - By Priority
No-Need Features Text List - By Priority-
Brand Recognition Text List
Consumer Segmentation Text Table
'Volume' of Positive Feedback Integer
Volume' of Negative Feedback Integer
Opinion Influencers' Feedback Text List
High Caliber Bloggers' Feedback Text List
Consumer Feedback about Pricing Text List
Consumer Feedback about Packaging Text List
Consumer Feedback about Innovation Text List
Consumer Feedback about Technology Text List
Consumer Feedback about Compliancy Text List
Consumer Feedback about Regulatory Text List
Consumer Feedback by Age Text Table
Consumer Feedback by Geographic Text Table
Consumer Feedback by Ethnic Text Table
Consumer Feedback by Economic Text Table
Consumer Feedback by Education Text Table
Feedback on Competitive Brands Text List
Table: All the above fields
Competitors
about each competitor
Table 3
Fig. 6 schematically illustrates a 3-dimenal matrix the outlines the CNMD 124, according to an embodiment of the invention. CNMD 124 may include data representing Customer-Related information such as Annual/Quarterly Growth Rate, Annual/Quarterly Revenues, Annual/Quarterly Sales, Annual/Quarterly Gross Profit, Annual/Quarterly Operating Profit, Equity Capital, Operating Capital, Revenue per Share, Multiplier, CAGR (Compound Annual Growth Rate), EBITDA (Earning Before Interest, Tax, Depreciation and Amortization), etc.
The following Table 4 outlines an exemplary data type of different fields that may be included in CNMD 124:
Table 4
An exemplary IP related data is shown by following Table 5:
Table 5
The following provides descriptions of the subsystem modules that work with CAAD 120 in order to provide a suitable computing environment in which the invention may be implemented. While the invention will be described in the general context of program modules that execute in conjunction with an application program that runs on an operating system on a computer system, those skilled in the art will recognize that the invention may also be implemented in combination with other subsystem modules.
Database Manager
Keeps all the databases within system 100 - that is, the UMMD 121, SMMD 122, CNMD 123, and CSMM 124 - updated, consistent, and complete - using various tools, like:
- Editors - Graphical software enabling intuitive insertion, deletion, modification, and visualization of formatted data of various types like text, graphics, audio, video, etc.
- Events Manager— A software module that allows performing basic tasks with databases, like Create, Delete, Update, Insert, Open, Save, Alert, Drop, Logon, Logoff, Startup, Shutdown, etc., as well as accessing records and fields within a database.
- Triggers Manager - A software module maintaining the integrity of the information on the databases, by containing stored procedures that configured to automatically execute in response to certain events take place on particular table or view in a database.
Validator
The validator 102 validates the expected metrics of a Marketing Strategy/Commercial Campaign by examining their correlation with predefined reference metrics of system 100, and fine tuning these values accordingly. In Addition, it ensures that the current Marketing Strategy/Commercial Campaign is constantly valid and reliable - and notifying the Decision Maker module accordingly.
One of the core elements of system 100 is a Self-Learning mechanism which used to enhance both the validity and reliability of the system. Reliability is ensured by observing the overall consistency and repeatability of the various measures/metrics and checking if they produce similar results under consistent conditions.
According to an embodiment of the invention, the reference metrics can be a pre-modeling marketing data having a plurality of marketing variables, wherein each of the plurality of marketing variables associated with marketing strategies for one or more products/services. Examples of the marketing variables include, but are not limited to, sales data captured over a period of time for products, parameters indicating the time/season of the year, macroeconomic parameters such as total income of individuals in a selected market region and marketing variables such as number of advertisements of the products through various communication channels, number of users visiting a Website of stores selling the products. It would be appreciated by those skilled in the art that a variety of such marketing parameters may be envisaged.
Marketing Strategy Analyzer
Strategy Analyzer 103 analyzes on-line the entire marketing strategy for providing results at each single criteria of a marketing strategy, such as brand (product or service) perception, brand strengths and weaknesses, key opinion leader mapping, market's real needs and
unaddressed consumers' needs, competitive intelligence (competitor and brand mapping, pricing, perception, strengths, weaknesses, innovation, technologies), competitors' reaction (offering, pricing, packaging, campaigns, etc.), market maturity indicators, market key drives and challenges, market disruptive trends, regulatory and compliancy indicators, technology landscape, innovation threats, IP (Intellectual Property) strengths and weaknesses, most attractive target markets, new opportunities, competitive brand positioning, best offering, most recommended business/strategic partnerships, etc.
Commercial Campaign Analyzer
Campaign Analyzer 104 performs on-line analyzing of an entire given commercial campaign, and accordingly it may provide data results for each single criteria of this commercial campaign.
Forecaster
Based on present values of various parameters - such as sales, consumer segmentation by various breakdowns, pricing, etc., Forecaster 105 computes the foreseen values of these parameters, and accordingly provides relevant trends, both domestic and international, that may affect the marketing strategy/commercial campaign.
Decision Maker
Decision Maker 106 provides critical business, strategic, and operational reactive decision making, based on Artificial Intelligence (AI) methodologies— such as improving go-to-market plan, hit market faster, marketing plan reassessment, pricing strategy reassessment, sales plan reassessment, sales force effectiveness, etc.— in the course of an active marketing strategy/commercial campaign - according to the results of Validator 102.
The Decision Maker module 106 enables the customer to respond across
all channels on-the-fly, in real time — while the marketing strategy/commercial campaign is running - and affecting the results accordingly, by changing/modifjdng the marketing strategy/commercial campaign.
Post-Mortem Analyzer
Post-Mortem Analyzer 107 performs offline comprehensive and in-depth analysis— at the end of the marketing strategy/commercial campaign of a specific sector - and accordingly amends the system predefined reference metrics of this sector:
- Correlation— calculating the correlation between the expected metrics and the system predefined reference metrics;
- Sectorial Standard Deviation - calculating the difference between the expected metrics and the system predefined reference metrics, relative to this difference in all the other marketing strategies/commercial campaigns of the same sector;
- Global Standard Deviation - calculating the difference between the expected metrics and the system predefined reference metrics, relative to this difference in all the other marketing strategies/commercial campaigns of all the sectors;
- Trends Identification;
- Non-Trivial Patterns - analyzing those patterns which need long time of observation and follow-up in order to conclude insights accordingly - such as phenomena happen only at a specific day in a month/week, or at a specific hour in a day, or at a specific geography, or for a very specific gender, etc.
Exploring the reasons for the above mentions correlation and standard deviations, according to variety of terms such as:
« Marketing strategy/commercial campaign launch time (e.g., month during the year, season during the year, any other special event during the year, etc.);
« Marketing Media Channels (e.g., Resellers, Retailers, Point of
Sales, Television, Cinema, Print media. Interactive Billboard, Social Networks, IVR [Interactive Voice Response]);
« Time Amount of Exposure to a Brand (Product or Service);
■ Socio-Economic Breakdowns;
■ Demographic Profile (e.g., Place of Living such as City/Town/Village, North/East/South/West, etc.);
• Income Level;
» Education Degree (e.g., Basic School/High School/Academy, etc.),
Gender (Female/Male);
« Marital Status (e.g., Single/Married/Divorced/Widow);
and the like. APIs
APIs 109 recognizes that every third party vendor has its own unique process and workflow requirements - this subsystem contains a set of open and fully standards compliant APIs (Application Programming Interface) providing the modularity to build a highly flexible best-in-class ecosystem.
This module may contain APIs with the following third party subs3^stems:
- Professional Databases 111, such as IP (Intellectual Properties), Trade, Finance, Governance, Academic Researches Publications, Regulatory
- A Social Media API module 110 that transforms multiple unclassified social online data - which is proven to be an ultimate source for intelligence— into purposeful intelligence findings:
• Measuring qualitative metrics — loyalty, trust, passion, interaction, and brand awareness
« Measuring quantitative metrics — reach, volume of posts, conversations surround the brand, and influencers engagement
The Social Media API module 110 gathers data that can be collected from a wide range of available web-based sources such as social networks, news
publications, magazines, high-caliber blogs, consumer discussions, career websites, etc. Interfacing with Social Media 110 enables to provide an analysis of the social conversation surround a product or service.
Administration Console
Administration Console 108 is software based application that provides a powerful graphical tool, which may enable the following:
- Setting/Modifying of system predefined reference metrics (Super User);
- Setting/Modifying of expected metrics given by the customer;
- Setting/Modifying of the weight of each taking part metric.
In addition, the Administration Console 108 provides an intuitive data visualization, in various breakdowns, that is easy to interpret and easy to act on— giving insights into the hearth of the system at variety of aspects, such as:
- Multi-Level (e.g., specific marketing media, a group of marketing media, entire marketing strategy life, entire commercial campaign life);
Multi-Period (e.g., Daily /Weekly /Monthly/Quarterly, entire marketing strategy/commercial campaign period, user defined);
- Multi-Format (e.g., table, pie chart, bar chart, graph).
Business and Marketing Insights
The business and marketing insights module 112 provides intuitive insights visualization that is easy to interpret and easy to act on - addressing a wide range of highly valuable business and marketing missions:
- Insights about current situation:
« Brand— Product or Service - Perception
» Brand Strengths and Weaknesses
« Key Opinion Leader Mapping
■ Market's Real Needs and Unaddressed Consumers' Needs
« Competitive Intelligence (e.g., Competitor and Brand Mapping, Pricing, Perception, Strengths, Weaknesses, Innovation, Technologies)
■ Competitors' Reaction (Offering, Pricing, Packaging, Campaigns, etc.)
• Market Maturity Indicators
» Market Key Drives and Challenges
■ Market Disruptive Trends
« Regulatory and Compliancy Indicators
■ Technology Landscape/Innovation Threats
« IP Strengths and Weaknesses
« Market Maturity Indicators
• Market Key Drives and Challenges
« Market Trends
- Regulatory and Compliancy Indicators
« Technology Landscape/Innovation Threats
■ IP Strengths and Weaknesses
Insights on Recommended Marketing Strategy/Commercial Campaign:
• Most Attractive Target Markets
« Most Attractive Target Markets
New Opportunities
« Competitive Brand Positioning
Best Offering
» Improving Go-To-Market Plan and Hit Market Faster
■ Marketing Plan Reassessment
« Pricing Strategy Reassessment
Sales Plan Reassessment
- Sales Force Effectiveness
« Most Recommended Business/Strategic Partnerships
Such insights enable maximizing the ROI (Return On Investment), capitalizing on marketing costs, by allowing system 100 to deliver the right message, at the right time, to the right audience, and by the right channels.
The Business and Marketing Insights module 112 may provide its outcomes in various breakdowns:
- Specific Country;
- A Group of Countries (e.g., EU [European Union], OECD [Organization for Economic Co-operation and Development], BRICS [Brazil, Russia, India, China, South Africa)], Developed Countries, Developing Countries, Worldwide);
Specific Brand (Product or Service);
- A Group of Brands (Products or Services);
- At Firm Level.
CAAD 120 and the subsystems modules of system 100 are implemented by program modules that may include routines, programs, components, data structures, and other t ^pes of structures that perform particular tasks or implement particular abstract data types in system 100. Moreover, those skilled in the art will appreciate that the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.
Embodiments of the invention may be implemented as a computer process (method), a computing system, or as an article of manufacture, such as a
computer program product or computer readable media. The computer program product may be a computer storage media readable by a computer system and encoding a computer program of instructions for executing a computer process. The computer program product may also be a propagated signal on a carrier readable by a computing system and encoding a computer program of instructions for executing a computer process.
Although the functions described hereinabove may be performed by executable code and instructions stored in computer readable medium and running on one or more processor -based systems. However, state machines, and/or hardwired electronic circuits can also be utilized. Further, with respect to the example processes described hereinabove, not all the process states need to be reached, nor do the states have to be performed in the illustrated order. Further, certain process states that are illustrated as being serially performed can be performed in parallel.
Fig. 7 schematically illustrates system 100 is a top level layer form, according to an embodiment of the invention. The layer form includes a data storage layer 73 that performs data mining using CAAD 120, a business logic laj^e 72 that perform data processing and a presentation layer 71 that provides the data to the user.
The terms, "for example", "e.g.", "optionally", as used herein, are intended to be used to introduce non-limiting examples. While certain references are made to certain example system subsystem modules or services, other subsystem modules and services can be used as well and/or the example subsystem modules can be combined into fewer components and/or divided into further components.
As will be appreciated by the skilled person the embodiments described hereinabove results in a cloud-based platform that converts information
and intelligence into ke}^ discoveries and actionable insights aligned with the customer's current and evolving business and marketing needs. Moreover it provides unique methodologies of research and intelligence analysis by automatically collecting diverse signals from various - static and dynamic - sources, then modeling, and integrating Human Intuition, expertise, and usable knowledge, thereby providing evidence-based, actionable insights to essential business questions.
All the above description and examples have been given for the purpose of illustration and are not intended to limit the invention in any way. Many different mechanisms, methods of analysis and subsystem modules can be employed, all without exceeding the scope of the invention.
Claims
1. A fully- automated method, in a data processing system, for defining and qualitatively measuring marketing strategies/commercial campaign, the method comprising:
a) dynamically obtaining — by a data mining subsystem — information related to marketing strategy/commercial campaign; b) analyzing - by a data processing subsystem— said information, in real-time and offline, to identify patterns;
c) selecting - by said data processing subsystem - relevant patterns from said identified patterns to define a marketing strategy/commercial campaign for a customer; and
d) defining— by said data processing subsystem— a marketing strategy/commercial campaign based on said selected patterns and addressed to a specific brand— product or service— of a specific customer, which playing in a specific sector, of a specific country, at a specific time.
2. The method according to claim 1, wherein obtaining information related to marketing strategy/commercial campaign further comprises: ensuring reliability and validating expected data metrics of a marketing strategy/commercial campaign— based on a self- learning mechanism - by examining their correlation with predefined reference metrics, and fine tuning these values accordingly, thereby ensuring that the current marketing strategy/commercial campaign is constantly valid, reliable, efficient and qualitative measurability.
3. A method according to claim 2, further comprising applying artificial intelligent algorithms on the fine-tuned data— as part of the self-learning mechanism— thereby providing valid and reliable strategic.
4. The method according to claim 1, wherein obtaining information related to marketing strategy/commercial campaign comprises: performing data mining operations to collect customer interaction information from a plurality of sources - both in real-time (online) and offline.
5. The method according to claim 4, wherein the data mining operations comprise data retrieval form external sources including Social Media and Professional Databases.
6. The method according to claim 4, wherein the customer interactions comprise at least one of a brand— Product or Service— review, a review comment, a post, a comment, various types of digital feedbacks, or interconnected documents and other digital conversations.
7. The method according to claim 4, wherein analyzing the information to identify patterns comprises: identifying parameters based on their current values and computing foreseen values of these parameters, and accordingly providing relevant trends - business, commercial, trade, geo-locational, geographic, demographic, and psychographic - both domestic and international, that may affect the marketing strategy/commercial campaign.
8. The method according to claim 7, wherein analyzing the information to identify patterns further comprises: analyzing the parameters at the end of the marketing strategy/commercial campaign of a specific sector and amending the system predefined reference metrics of this sector accordingly— as known as Post- Mortem Analysis, thereby ensuring validity and reliability.
9. The method according to claim 1, wherein analyzing the
information to identif}^ patterns comprises: qualitatively and efficiently identifying a set of influencing parameters, wherein the set of influencing parameters is used by a vendor to define marketing strategies for a set of customers.
10. A method according to claim 1, further comprising allowing the integration of human intuition, expertise, and usable knowledge, and accordingly providing most up-to-date, valid, and reliable Marketing Strategy/Commercial Campaign.
11. A method according to claim 1, further comprising creating evidence-based, actionable insights to essential business questions, by the data processing and data mining.
12. A method according to claim 11, wherein the creation of the actionable insights includes one or more of: fully-automated and continually gathering information from many sources - both in real time and offline, capturing a 360 degree view around the product or service, monitoring the social conversation surround the product/service, filtering the top relevant information only, identifying hidden patterns - by analyzing huge amount of information and intelligence, and over long time, in-depth, competitive analysis, continually analyzing/reanalyzing the information, and comparing the results to the real world— ensuring the system is always valid and reliable, micro-assessment of strengths, weaknesses, opportunities, an threats, identifying and alerting vulnerabilities, identifying and alerting edge advantages, minimizing risks and maximizing opportunities by early discovering and alerting, reactive decision making, Post-Mortem analysis— enhancing the validity and reliability of the system, cross-checking with insights generated for other analysis of the same sector and/or country - enhancing the validity and reliability of the system.
13. A method according to claim 2, further comprising providing an operational Reactive Decision Making module while the marketing strategy/commercial campaign is running, thereby enabling responding - across all channels— on-the-fly, changing/modifying the marketing strategy/commercial campaign in real time, and affecting the results accordingly.
14. A method according to claim 1, wherein fully-automatically and qualitatively defining a marketing strategy based on the selected patterns comprises: dynamically identifying at least one of channels associated with a segment of brands either products or services; identifying marketing strategies of a vendor associated with a segment of brands based on current business, commercial, trade, geo-locational, geographic, demographic, and psychographic factors that are associated with a customer and a most efficient channel to reach the customer for the segment of said brands; and presenting to a client associated with a customer, a set of marketing strategies defined by a vendor for the segment of said brands as a ranked list.
15. A system, comprising:
a) at least one processor; and b) a memory comprising computer-readable instructions which when executed by the at least one processor causes the processor to execute a data processing system for defining and qualitatively measuring marketing strategies/commercial campaign, wherein the system:
- dynamically obtains— by a data mining subsystem - information related to marketing strategy/commercial campaign;
analyzes — by a data processing subsystem — said information, in real-time and offline, to identif}^ patterns; selects— by said data processing subsystem— relevant patterns from said identified patterns to define a marketing strategy/commercial campaign for a customer; and
defines— by said data processing subsystem - a marketing strategy/commercial campaign based on said selected patterns and addressed to a specific brand— product or service - of a specific customer, which playing in a specific sector, of a specific country, at a specific time.
16. A non-transitory computer-readable medium comprising instructions which when executed by at least one processor causes the processor to perform the method of claim 1.
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
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CN201580078632.2A CN107533710A (en) | 2015-04-08 | 2015-04-08 | For fully automatically qualitative planning, effectively measurement, formulation and subsidy business strategy and the method and system of business activity |
EP15888389.2A EP3281167A4 (en) | 2015-04-08 | 2015-04-08 | Qualitatively planning, measuring, making effecient and capitalizing on marketing strategy |
PCT/IL2015/050382 WO2016162863A1 (en) | 2015-04-08 | 2015-04-08 | Qualitatively planning, measuring, making effecient and capitalizing on marketing strategy |
IL254860A IL254860B (en) | 2015-04-08 | 2017-10-02 | Method and system for fully-automated and qualitatively planning, measuring, making efficient and capitalizing on business strategies and marketing strategies |
US15/722,489 US20180025394A1 (en) | 2015-04-08 | 2017-10-02 | Qualitatively planning, measuring, making efficient and capitalizing on marketing strategy |
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PCT/IL2015/050382 WO2016162863A1 (en) | 2015-04-08 | 2015-04-08 | Qualitatively planning, measuring, making effecient and capitalizing on marketing strategy |
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US15/722,489 Continuation-In-Part US20180025394A1 (en) | 2015-04-08 | 2017-10-02 | Qualitatively planning, measuring, making efficient and capitalizing on marketing strategy |
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WO2016162863A1 true WO2016162863A1 (en) | 2016-10-13 |
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EP (1) | EP3281167A4 (en) |
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WO (1) | WO2016162863A1 (en) |
Cited By (6)
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CN109377276A (en) * | 2018-10-17 | 2019-02-22 | 南京高鸿未来网络科技有限公司 | A kind of electric business marketing system based on big data analysis |
CN111738763A (en) * | 2020-06-19 | 2020-10-02 | 京东数字科技控股有限公司 | Policy processing method, device, equipment and storage medium |
CN113781129A (en) * | 2021-11-15 | 2021-12-10 | 百融至信(北京)征信有限公司 | Intelligent marketing strategy generation method and system |
CN113793001A (en) * | 2021-09-01 | 2021-12-14 | 国家电网有限公司客户服务中心 | High-quality client competition strategy analysis method based on national network APP application |
CN115510328A (en) * | 2022-10-11 | 2022-12-23 | 江苏云机汇软件科技有限公司 | Commodity brand marketing data analysis method based on big data |
CN111738763B (en) * | 2020-06-19 | 2024-04-19 | 京东科技控股股份有限公司 | Policy processing method, device, equipment and storage medium |
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CN109003143A (en) * | 2018-08-03 | 2018-12-14 | 阿里巴巴集团控股有限公司 | Recommend using deeply study the method and device of marketing |
US20220067623A1 (en) * | 2020-08-26 | 2022-03-03 | International Business Machines Corporation | Evaluate demand and project go-to-market resources |
CN112116215A (en) * | 2020-08-28 | 2020-12-22 | 国网福建省电力有限公司 | Multi-dimensional electric charge recovery index monitoring method |
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Also Published As
Publication number | Publication date |
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IL254860A0 (en) | 2017-12-31 |
EP3281167A4 (en) | 2018-10-31 |
CN107533710A (en) | 2018-01-02 |
EP3281167A1 (en) | 2018-02-14 |
IL254860B (en) | 2021-12-01 |
US20180025394A1 (en) | 2018-01-25 |
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